code: def accuracy_score(prediction, groundtruth):
      FP, FN, TP, TN = numeric_score(prediction, groundtruth)
      N = FP + FN + TP + TN
      accuracy = np.divide(TP + TN, N)
      return accuracy * 100.0
  
file_path: medicaltorch/medicaltorch/metrics.py
imports: from collections import defaultdict
  from scipy import spatial
  import numpy
label_desc: Use image node_id 9 for calling a global function with example usage: accuracy_score(prediction, groundtruth) and returns: unknown